Compare NEXRAD Radar with KAZR
Contents
Compare NEXRAD Radar with KAZR#
Within this notebook, we will look at comparing NEXRAD data with data collected from the KAZR radar (vertically pointing)
Data#
We have two data sources:
NEXRAD Data#
NEXRAD data is stored on AWS through the Open Data Initiative
There is a specific Python package called nexradaws, which makes working with these data easier!
The nearest NEXRAD radars to the TRACER field campaign are:
We will be accessing data on the NEXRAD AWS Bucket (maintained by Unidata)
KAZR Data#
The KAZR data explored here is exploratory and has not been calibrated, indicating that it is not meant to be used for analysis, but rather a proof-of-concept. It is a vertically pointing Ka-band radar.
From the official ARM KAZR Documentation, “The Ka-band ARM zenith radar (KAZR) remotely probes the extent and composition of clouds at millimeter wavelengths. The KAZR is a zenith-pointing Doppler radar that operates at a frequency of approximately 35 GHz. The main purpose of this radar is to determine the first three Doppler moments (reflectivity, vertical velocity, and spectral width) at a range resolution of approximately 30 meters from near-ground to nearly 20 km in altitude.”
After finding data on the ARM Data Hub using this query, download the data and place in some data directory!
Imports#
import xarray as xr
import pyart
import nexradaws
import tempfile
from datetime import datetime
import pytz
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
from distributed import LocalCluster, Client
import numpy as np
import xcollection as xc
import cartopy.feature as cfeature
import hvplot.xarray
import holoviews as hv
import warnings
warnings.filterwarnings("ignore")
hv.extension('bokeh')
cluster = LocalCluster()
client = Client(cluster)
client
2022-03-23 12:35:37,240 - distributed.diskutils - INFO - Found stale lock file and directory '/Users/mgrover/git_repos/tracer-radar-analysis/notebooks/march-22-2022/dask-worker-space/worker-752c9wb7', purging
2022-03-23 12:35:37,242 - distributed.diskutils - INFO - Found stale lock file and directory '/Users/mgrover/git_repos/tracer-radar-analysis/notebooks/march-22-2022/dask-worker-space/worker-fy_90cvl', purging
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2022-03-23 12:35:37,243 - distributed.diskutils - INFO - Found stale lock file and directory '/Users/mgrover/git_repos/tracer-radar-analysis/notebooks/march-22-2022/dask-worker-space/worker-yjd669ot', purging
2022-03-23 12:35:37,243 - distributed.diskutils - INFO - Found stale lock file and directory '/Users/mgrover/git_repos/tracer-radar-analysis/notebooks/march-22-2022/dask-worker-space/worker-4odlboz9', purging
2022-03-23 12:35:37,244 - distributed.diskutils - INFO - Found stale lock file and directory '/Users/mgrover/git_repos/tracer-radar-analysis/notebooks/march-22-2022/dask-worker-space/worker-ib4c6d9k', purging
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2022-03-23 12:35:37,246 - distributed.diskutils - INFO - Found stale lock file and directory '/Users/mgrover/git_repos/tracer-radar-analysis/notebooks/march-22-2022/dask-worker-space/worker-2ixfjb7f', purging
2022-03-23 12:35:37,247 - distributed.diskutils - INFO - Found stale lock file and directory '/Users/mgrover/git_repos/tracer-radar-analysis/notebooks/march-22-2022/dask-worker-space/worker-6a7n_3s5', purging
Client
Client-a6e75608-aacf-11ec-95bb-acde48001122
| Connection method: Cluster object | Cluster type: distributed.LocalCluster |
| Dashboard: http://127.0.0.1:8787/status |
Cluster Info
LocalCluster
a09a9146
| Dashboard: http://127.0.0.1:8787/status | Workers: 4 |
| Total threads: 12 | Total memory: 16.00 GiB |
| Status: running | Using processes: True |
Scheduler Info
Scheduler
Scheduler-1b62bf3b-031b-4ca8-90f8-fdfadef3785c
| Comm: tcp://127.0.0.1:49636 | Workers: 4 |
| Dashboard: http://127.0.0.1:8787/status | Total threads: 12 |
| Started: Just now | Total memory: 16.00 GiB |
Workers
Worker: 0
| Comm: tcp://127.0.0.1:49648 | Total threads: 3 |
| Dashboard: http://127.0.0.1:49652/status | Memory: 4.00 GiB |
| Nanny: tcp://127.0.0.1:49640 | |
| Local directory: /Users/mgrover/git_repos/tracer-radar-analysis/notebooks/march-22-2022/dask-worker-space/worker-9j_db1lu | |
Worker: 1
| Comm: tcp://127.0.0.1:49647 | Total threads: 3 |
| Dashboard: http://127.0.0.1:49651/status | Memory: 4.00 GiB |
| Nanny: tcp://127.0.0.1:49641 | |
| Local directory: /Users/mgrover/git_repos/tracer-radar-analysis/notebooks/march-22-2022/dask-worker-space/worker-5h2flwn2 | |
Worker: 2
| Comm: tcp://127.0.0.1:49649 | Total threads: 3 |
| Dashboard: http://127.0.0.1:49650/status | Memory: 4.00 GiB |
| Nanny: tcp://127.0.0.1:49639 | |
| Local directory: /Users/mgrover/git_repos/tracer-radar-analysis/notebooks/march-22-2022/dask-worker-space/worker-x56h0urf | |
Worker: 3
| Comm: tcp://127.0.0.1:49656 | Total threads: 3 |
| Dashboard: http://127.0.0.1:49657/status | Memory: 4.00 GiB |
| Nanny: tcp://127.0.0.1:49642 | |
| Local directory: /Users/mgrover/git_repos/tracer-radar-analysis/notebooks/march-22-2022/dask-worker-space/worker-oje457is | |
Access NEXRAD Data#
We can use the NexradAwsInterface class from nexradaws to acces the data, using the following steps:
Establish an initial connection
Query/subset for our desired site/time
Download to some directory
#https://stackoverflow.com/questions/32237862/find-the-closest-date-to-a-given-date/32237949
def nearest(items, pivot):
return min(items, key=lambda x: abs(x - pivot))
def download_radar_data(site='KLOT',
cache_location=tempfile.mkdtemp(),
target_time=datetime.utcnow()):
"""
Accesses data from AWS S3
Parameters
----------
site: str, default='KLOT' (Chicago)
Site to download data from (ex. 'KLOT')
cache_location: str, default=tempfile.mkdtemp()
Where to place the cached data files
target_time: datetime.datetime, default=datetime.utcnow()
Time index to search for
Returns
-------
file : str
Path to the NEXRAD file
"""
# Convert the datetime to UTC
target_time = target_time.astimezone(pytz.utc)
# Setup the initial connection
aws_connection = nexradaws.NexradAwsInterface()
# Check for available scans
scans = aws_connection.get_avail_scans(target_time.year,
target_time.month,
target_time.day,
site)
# Retrieve the scan times
scan_times = [scan.scan_time for scan in scans]
# Loop through and find good scans
good_scans = []
good_times = []
for i in range(len(scans)):
if scan_times[i] is not None:
good_times.append(scan_times[i])
good_scans.append(scans[i])
print(f'Found {len(good_scans)} good scans')
print(f'Found {len(good_times)} good times')
# Find the nearest time using our helper function
nearest_time = nearest(good_times, target_time)
# Locate closest time in our scans
closest_time_index = good_times.index(nearest_time)
# Download the file
file = aws_connection.download(good_scans[closest_time_index],
f'{cache_location}/{site}')
# Return the filepath
return file.success[0].filepath
Download the file#
time = datetime(2022, 3, 21, 7, 55, 0)
KLCH_file = download_radar_data(site='KLCH',
cache_location='/Volumes/Samsung_T5/argonne/nexrad-data',
target_time=time)
KHGX_file = download_radar_data(site='KHGX',
cache_location='/Volumes/Samsung_T5/argonne/nexrad-data',
target_time=time)
Found 235 good scans
Found 235 good times
Downloaded KLCH20220321_125135_V06
1 out of 1 files downloaded...0 errors
Found 296 good scans
Found 296 good times
Downloaded KHGX20220321_125323_V06
1 out of 1 files downloaded...0 errors
Run Through the Analysis#
Now that we have the data, let’s start our analysis!
Convert to an Xarray Object#
We add a couple of helper functions to convert each sweep to a dataset, then the full volume to a dictionary of datasets
def create_dataset_from_sweep(radar, sweep=0, field=None):
"""
Creates an xarray.Dataset from sweeps
"""
# Grab the range
range = radar.range['data']
# Grab the elevation
elevation = radar.get_elevation(sweep)
# Grab the azimuth
azimuth = radar.get_azimuth(sweep)
# Grab the x, y, z values
x, y, z = radar.get_gate_x_y_z(sweep)
# Grab the lat, lon, and elevation
lat, lon, alt = radar.get_gate_lat_lon_alt(sweep)
# Add the fields
field_dict = {}
for field in list(radar.fields):
field_dict[field]=(["azimuth", "range"], radar.get_field(sweep, field))
ds = xr.Dataset(
data_vars=field_dict,
coords=dict(
x=(["azimuth", "range"], x),
y=(["azimuth", "range"], y),
z=(["azimuth", "range"], z),
lat=(["azimuth", "range"], lat),
lon=(["azimuth", "range"], lon),
alt=(["azimuth", "range"], alt),
azimuth=azimuth,
elevation=elevation,
sweep=np.array([sweep]),
range=range),
)
return ds.chunk()
Create an “Xradar” object#
For now, we utilize xcollection which is a dictionary of datasets with some added functionality
def convert_to_xradar(radar):
"""
Converts from radar to xradar
"""
ds_list = []
sweeps = radar.sweep_number['data']
for sweep in sweeps:
ds_list.append(create_dataset_from_sweep(radar, sweep))
# Convert the numpy array to a list of strings
dict_keys = [x for x in list(sweeps.astype(str))]
# Zip the keys and datasets and turn into a dictionary
dict_of_dsets = dict(zip(dict_keys, ds_list))
return xc.Collection(dict_of_dsets)
Run our workflow#
Read the data into PyART#
klch_radar = pyart.io.read(KLCH_file)
khgz_radar = pyart.io.read(KHGX_file)
klch_radar.time['units']
'seconds since 2022-03-21T12:51:35Z'
Convert to Xradar#
klch_xradar = convert_to_xradar(klch_radar)
khgz_xradar = convert_to_xradar(khgz_radar)
klch_xradar['0']
- 🔑 0
<xarray.Dataset> Dimensions: (azimuth: 720, range: 1832, elevation: 720, sweep: 1) Coordinates: x (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> y (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> z (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> lat (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> lon (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> alt (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> * azimuth (azimuth) float64 7.251 7.748 ... 6.254 6.748 * elevation (elevation) float32 0.5136 0.5466 ... 0.4834 * sweep (sweep) int32 0 * range (range) float32 2.125e+03 ... 4.599e+05 Data variables: differential_phase (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> spectrum_width (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> cross_correlation_ratio (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> clutter_filter_power_removed (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> differential_reflectivity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> velocity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> reflectivity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray>xarray.Dataset- azimuth: 720
- range: 1832
- elevation: 720
- sweep: 1
- x(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - y(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - z(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - lat(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - lon(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - alt(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - azimuth(azimuth)float647.251 7.748 8.253 ... 6.254 6.748
array([7.250977, 7.748108, 8.253479, ..., 5.756836, 6.253967, 6.748352])
- elevation(elevation)float320.5136 0.5466 ... 0.4834 0.4834
array([0.513611, 0.54657 , 0.535583, ..., 0.483398, 0.483398, 0.483398], dtype=float32) - sweep(sweep)int320
array([0], dtype=int32)
- range(range)float322.125e+03 2.375e+03 ... 4.599e+05
array([ 2125., 2375., 2625., ..., 459375., 459625., 459875.], dtype=float32)
- differential_phase(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - spectrum_width(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - cross_correlation_ratio(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - clutter_filter_power_removed(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - differential_reflectivity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - velocity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - reflectivity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray
- 🔑 1
<xarray.Dataset> Dimensions: (azimuth: 720, range: 1832, elevation: 720, sweep: 1) Coordinates: x (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> y (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> z (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> lat (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> lon (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> alt (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> * azimuth (azimuth) float64 18.21 18.69 ... 17.2 17.69 * elevation (elevation) float32 0.4834 0.4834 ... 0.4834 * sweep (sweep) int32 1 * range (range) float32 2.125e+03 ... 4.599e+05 Data variables: differential_phase (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> spectrum_width (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> cross_correlation_ratio (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> clutter_filter_power_removed (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> differential_reflectivity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> velocity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> reflectivity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray>xarray.Dataset- azimuth: 720
- range: 1832
- elevation: 720
- sweep: 1
- x(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - y(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - z(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - lat(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - lon(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - alt(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - azimuth(azimuth)float6418.21 18.69 19.2 ... 17.2 17.69
array([18.209839, 18.693237, 19.195862, ..., 16.712952, 17.20459 , 17.690735])
- elevation(elevation)float320.4834 0.4834 ... 0.4834 0.4834
array([0.483398, 0.483398, 0.483398, ..., 0.483398, 0.483398, 0.483398], dtype=float32) - sweep(sweep)int321
array([1], dtype=int32)
- range(range)float322.125e+03 2.375e+03 ... 4.599e+05
array([ 2125., 2375., 2625., ..., 459375., 459625., 459875.], dtype=float32)
- differential_phase(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - spectrum_width(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - cross_correlation_ratio(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - clutter_filter_power_removed(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - differential_reflectivity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - velocity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - reflectivity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray
- 🔑 2
<xarray.Dataset> Dimensions: (azimuth: 720, range: 1832, elevation: 720, sweep: 1) Coordinates: x (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> y (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> z (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> lat (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> lon (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> alt (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> * azimuth (azimuth) float64 33.28 33.75 ... 32.24 32.75 * elevation (elevation) float32 0.8569 0.835 ... 0.835 * sweep (sweep) int32 2 * range (range) float32 2.125e+03 ... 4.599e+05 Data variables: differential_phase (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> spectrum_width (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> cross_correlation_ratio (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> clutter_filter_power_removed (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> differential_reflectivity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> velocity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> reflectivity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray>xarray.Dataset- azimuth: 720
- range: 1832
- elevation: 720
- sweep: 1
- x(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - y(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - z(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - lat(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - lon(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - alt(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - azimuth(azimuth)float6433.28 33.75 34.25 ... 32.24 32.75
array([33.277588, 33.752747, 34.249878, ..., 31.750488, 32.244873, 32.747498])
- elevation(elevation)float320.8569 0.835 0.8212 ... 0.835 0.835
array([0.856934, 0.834961, 0.821228, ..., 0.834961, 0.834961, 0.834961], dtype=float32) - sweep(sweep)int322
array([2], dtype=int32)
- range(range)float322.125e+03 2.375e+03 ... 4.599e+05
array([ 2125., 2375., 2625., ..., 459375., 459625., 459875.], dtype=float32)
- differential_phase(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - spectrum_width(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - cross_correlation_ratio(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - clutter_filter_power_removed(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - differential_reflectivity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - velocity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - reflectivity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray
- 🔑 3
<xarray.Dataset> Dimensions: (azimuth: 720, range: 1832, elevation: 720, sweep: 1) Coordinates: x (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> y (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> z (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> lat (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> lon (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> alt (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> * azimuth (azimuth) float64 44.22 44.71 ... 43.22 43.72 * elevation (elevation) float32 0.835 0.835 ... 0.835 * sweep (sweep) int32 3 * range (range) float32 2.125e+03 ... 4.599e+05 Data variables: differential_phase (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> spectrum_width (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> cross_correlation_ratio (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> clutter_filter_power_removed (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> differential_reflectivity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> velocity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> reflectivity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray>xarray.Dataset- azimuth: 720
- range: 1832
- elevation: 720
- sweep: 1
- x(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - y(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - z(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - lat(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - lon(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - alt(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - azimuth(azimuth)float6444.22 44.71 45.2 ... 43.22 43.72
array([44.217224, 44.711609, 45.197754, ..., 42.714844, 43.220215, 43.720093])
- elevation(elevation)float320.835 0.835 0.835 ... 0.835 0.835
array([0.834961, 0.834961, 0.834961, ..., 0.834961, 0.834961, 0.834961], dtype=float32) - sweep(sweep)int323
array([3], dtype=int32)
- range(range)float322.125e+03 2.375e+03 ... 4.599e+05
array([ 2125., 2375., 2625., ..., 459375., 459625., 459875.], dtype=float32)
- differential_phase(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - spectrum_width(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - cross_correlation_ratio(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - clutter_filter_power_removed(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - differential_reflectivity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - velocity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - reflectivity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray
- 🔑 4
<xarray.Dataset> Dimensions: (azimuth: 720, range: 1832, elevation: 720, sweep: 1) Coordinates: x (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> y (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> z (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> lat (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> lon (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> alt (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> * azimuth (azimuth) float64 57.25 57.73 ... 56.26 56.75 * elevation (elevation) float32 1.305 1.258 ... 1.274 * sweep (sweep) int32 4 * range (range) float32 2.125e+03 ... 4.599e+05 Data variables: differential_phase (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> spectrum_width (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> cross_correlation_ratio (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> clutter_filter_power_removed (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> differential_reflectivity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> velocity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> reflectivity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray>xarray.Dataset- azimuth: 720
- range: 1832
- elevation: 720
- sweep: 1
- x(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - y(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - z(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - lat(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - lon(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - alt(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - azimuth(azimuth)float6457.25 57.73 58.25 ... 56.26 56.75
array([57.249756, 57.727661, 58.249512, ..., 55.750122, 56.255493, 56.749878])
- elevation(elevation)float321.305 1.258 1.25 ... 1.274 1.274
array([1.304626, 1.257935, 1.249695, ..., 1.274414, 1.274414, 1.274414], dtype=float32) - sweep(sweep)int324
array([4], dtype=int32)
- range(range)float322.125e+03 2.375e+03 ... 4.599e+05
array([ 2125., 2375., 2625., ..., 459375., 459625., 459875.], dtype=float32)
- differential_phase(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - spectrum_width(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - cross_correlation_ratio(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - clutter_filter_power_removed(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - differential_reflectivity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - velocity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - reflectivity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray
- 🔑 5
<xarray.Dataset> Dimensions: (azimuth: 720, range: 1832, elevation: 720, sweep: 1) Coordinates: x (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> y (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> z (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> lat (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> lon (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> alt (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> * azimuth (azimuth) float64 68.22 68.71 ... 67.21 67.7 * elevation (elevation) float32 1.274 1.274 ... 1.274 * sweep (sweep) int32 5 * range (range) float32 2.125e+03 ... 4.599e+05 Data variables: differential_phase (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> spectrum_width (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> cross_correlation_ratio (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> clutter_filter_power_removed (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> differential_reflectivity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> velocity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> reflectivity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray>xarray.Dataset- azimuth: 720
- range: 1832
- elevation: 720
- sweep: 1
- x(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - y(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - z(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - lat(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - lon(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - alt(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - azimuth(azimuth)float6468.22 68.71 69.19 ... 67.21 67.7
array([68.219604, 68.708496, 69.186401, ..., 66.717224, 67.211609, 67.695007])
- elevation(elevation)float321.274 1.274 1.274 ... 1.274 1.274
array([1.274414, 1.274414, 1.274414, ..., 1.274414, 1.274414, 1.274414], dtype=float32) - sweep(sweep)int325
array([5], dtype=int32)
- range(range)float322.125e+03 2.375e+03 ... 4.599e+05
array([ 2125., 2375., 2625., ..., 459375., 459625., 459875.], dtype=float32)
- differential_phase(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - spectrum_width(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - cross_correlation_ratio(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - clutter_filter_power_removed(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - differential_reflectivity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - velocity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - reflectivity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray
- 🔑 6
<xarray.Dataset> Dimensions: (azimuth: 720, range: 1832, elevation: 720, sweep: 1) Coordinates: x (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> y (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> z (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> lat (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> lon (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> alt (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> * azimuth (azimuth) float64 81.25 81.75 ... 80.25 80.75 * elevation (elevation) float32 0.4367 0.4449 ... 0.4834 * sweep (sweep) int32 6 * range (range) float32 2.125e+03 ... 4.599e+05 Data variables: differential_phase (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> spectrum_width (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> cross_correlation_ratio (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> clutter_filter_power_removed (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> differential_reflectivity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> velocity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> reflectivity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray>xarray.Dataset- azimuth: 720
- range: 1832
- elevation: 720
- sweep: 1
- x(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - y(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - z(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - lat(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - lon(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - alt(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - azimuth(azimuth)float6481.25 81.75 82.25 ... 80.25 80.75
array([81.252136, 81.749268, 82.246399, ..., 79.747009, 80.246887, 80.749512])
- elevation(elevation)float320.4367 0.4449 ... 0.4834 0.4834
array([0.436707, 0.444946, 0.472412, ..., 0.483398, 0.483398, 0.483398], dtype=float32) - sweep(sweep)int326
array([6], dtype=int32)
- range(range)float322.125e+03 2.375e+03 ... 4.599e+05
array([ 2125., 2375., 2625., ..., 459375., 459625., 459875.], dtype=float32)
- differential_phase(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - spectrum_width(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - cross_correlation_ratio(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - clutter_filter_power_removed(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - differential_reflectivity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - velocity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - reflectivity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray
- 🔑 7
<xarray.Dataset> Dimensions: (azimuth: 720, range: 1832, elevation: 720, sweep: 1) Coordinates: x (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> y (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> z (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> lat (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> lon (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> alt (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray> * azimuth (azimuth) float64 92.21 92.72 ... 91.22 91.72 * elevation (elevation) float32 0.4834 0.4834 ... 0.4834 * sweep (sweep) int32 7 * range (range) float32 2.125e+03 ... 4.599e+05 Data variables: differential_phase (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> spectrum_width (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> cross_correlation_ratio (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> clutter_filter_power_removed (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> differential_reflectivity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> velocity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray> reflectivity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray>xarray.Dataset- azimuth: 720
- range: 1832
- elevation: 720
- sweep: 1
- x(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - y(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - z(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - lat(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - lon(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - alt(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - azimuth(azimuth)float6492.21 92.72 93.23 ... 91.22 91.72
array([92.205505, 92.721863, 93.232727, ..., 90.703125, 91.219482, 91.722107])
- elevation(elevation)float320.4834 0.4834 ... 0.4834 0.4834
array([0.483398, 0.483398, 0.483398, ..., 0.483398, 0.483398, 0.483398], dtype=float32) - sweep(sweep)int327
array([7], dtype=int32)
- range(range)float322.125e+03 2.375e+03 ... 4.599e+05
array([ 2125., 2375., 2625., ..., 459375., 459625., 459875.], dtype=float32)
- differential_phase(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - spectrum_width(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - cross_correlation_ratio(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - clutter_filter_power_removed(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - differential_reflectivity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - velocity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - reflectivity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray
- 🔑 8
<xarray.Dataset> Dimensions: (azimuth: 360, range: 1832, elevation: 360, sweep: 1) Coordinates: x (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> y (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> z (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> lat (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> lon (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> alt (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> * azimuth (azimuth) float64 112.5 113.5 ... 110.5 111.5 * elevation (elevation) float32 1.887 1.862 ... 1.758 * sweep (sweep) int32 8 * range (range) float32 2.125e+03 ... 4.599e+05 Data variables: differential_phase (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> spectrum_width (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> cross_correlation_ratio (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> clutter_filter_power_removed (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> differential_reflectivity (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> velocity (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> reflectivity (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray>xarray.Dataset- azimuth: 360
- range: 1832
- elevation: 360
- sweep: 1
- x(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - y(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - z(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - lat(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - lon(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - alt(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - azimuth(azimuth)float64112.5 113.5 114.5 ... 110.5 111.5
array([112.543945, 113.549194, 114.54895 , ..., 109.547424, 110.549927, 111.546936]) - elevation(elevation)float321.887 1.862 1.837 ... 1.758 1.758
array([1.886902, 1.862183, 1.837463, ..., 1.757812, 1.757812, 1.757812], dtype=float32) - sweep(sweep)int328
array([8], dtype=int32)
- range(range)float322.125e+03 2.375e+03 ... 4.599e+05
array([ 2125., 2375., 2625., ..., 459375., 459625., 459875.], dtype=float32)
- differential_phase(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - spectrum_width(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - cross_correlation_ratio(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - clutter_filter_power_removed(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - differential_reflectivity(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - velocity(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - reflectivity(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray
- 🔑 9
<xarray.Dataset> Dimensions: (azimuth: 360, range: 1832, elevation: 360, sweep: 1) Coordinates: x (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> y (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> z (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> lat (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> lon (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> alt (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> * azimuth (azimuth) float64 127.6 128.6 ... 125.6 126.6 * elevation (elevation) float32 2.296 2.346 ... 2.373 * sweep (sweep) int32 9 * range (range) float32 2.125e+03 ... 4.599e+05 Data variables: differential_phase (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> spectrum_width (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> cross_correlation_ratio (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> clutter_filter_power_removed (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> differential_reflectivity (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> velocity (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> reflectivity (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray>xarray.Dataset- azimuth: 360
- range: 1832
- elevation: 360
- sweep: 1
- x(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - y(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - z(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - lat(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - lon(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - alt(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - azimuth(azimuth)float64127.6 128.6 129.5 ... 125.6 126.6
array([127.556763, 128.551025, 129.509583, ..., 124.552002, 125.559998, 126.551514]) - elevation(elevation)float322.296 2.346 2.362 ... 2.373 2.373
array([2.296143, 2.345581, 2.362061, ..., 2.373047, 2.373047, 2.373047], dtype=float32) - sweep(sweep)int329
array([9], dtype=int32)
- range(range)float322.125e+03 2.375e+03 ... 4.599e+05
array([ 2125., 2375., 2625., ..., 459375., 459625., 459875.], dtype=float32)
- differential_phase(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - spectrum_width(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - cross_correlation_ratio(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - clutter_filter_power_removed(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - differential_reflectivity(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - velocity(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - reflectivity(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray
- 🔑 10
<xarray.Dataset> Dimensions: (azimuth: 360, range: 1832, elevation: 360, sweep: 1) Coordinates: x (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> y (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> z (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> lat (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> lon (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> alt (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> * azimuth (azimuth) float64 144.5 145.5 ... 142.5 143.5 * elevation (elevation) float32 3.008 3.076 ... 3.076 * sweep (sweep) int32 10 * range (range) float32 2.125e+03 ... 4.599e+05 Data variables: differential_phase (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> spectrum_width (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> cross_correlation_ratio (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> clutter_filter_power_removed (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> differential_reflectivity (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> velocity (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> reflectivity (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray>xarray.Dataset- azimuth: 360
- range: 1832
- elevation: 360
- sweep: 1
- x(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - y(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - z(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - lat(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - lon(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - alt(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - azimuth(azimuth)float64144.5 145.5 146.6 ... 142.5 143.5
array([144.538879, 145.541382, 146.552124, ..., 141.539612, 142.536621, 143.54187 ]) - elevation(elevation)float323.008 3.076 3.109 ... 3.076 3.076
array([3.007507, 3.076172, 3.109131, ..., 3.076172, 3.076172, 3.076172], dtype=float32) - sweep(sweep)int3210
array([10], dtype=int32)
- range(range)float322.125e+03 2.375e+03 ... 4.599e+05
array([ 2125., 2375., 2625., ..., 459375., 459625., 459875.], dtype=float32)
- differential_phase(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - spectrum_width(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - cross_correlation_ratio(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - clutter_filter_power_removed(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - differential_reflectivity(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - velocity(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - reflectivity(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray
- 🔑 11
<xarray.Dataset> Dimensions: (azimuth: 360, range: 1832, elevation: 360, sweep: 1) Coordinates: x (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> y (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> z (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> lat (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> lon (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> alt (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> * azimuth (azimuth) float64 161.5 162.5 ... 159.5 160.5 * elevation (elevation) float32 3.84 3.911 ... 3.955 3.955 * sweep (sweep) int32 11 * range (range) float32 2.125e+03 ... 4.599e+05 Data variables: differential_phase (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> spectrum_width (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> cross_correlation_ratio (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> clutter_filter_power_removed (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> differential_reflectivity (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> velocity (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> reflectivity (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray>xarray.Dataset- azimuth: 360
- range: 1832
- elevation: 360
- sweep: 1
- x(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - y(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - z(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - lat(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - lon(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - alt(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - azimuth(azimuth)float64161.5 162.5 163.5 ... 159.5 160.5
array([161.542969, 162.545471, 163.547974, ..., 158.551941, 159.543457, 160.53772 ]) - elevation(elevation)float323.84 3.911 3.972 ... 3.955 3.955
array([3.839722, 3.911133, 3.971558, ..., 3.955078, 3.955078, 3.955078], dtype=float32) - sweep(sweep)int3211
array([11], dtype=int32)
- range(range)float322.125e+03 2.375e+03 ... 4.599e+05
array([ 2125., 2375., 2625., ..., 459375., 459625., 459875.], dtype=float32)
- differential_phase(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - spectrum_width(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - cross_correlation_ratio(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - clutter_filter_power_removed(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - differential_reflectivity(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - velocity(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - reflectivity(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray
- 🔑 12
<xarray.Dataset> Dimensions: (azimuth: 360, range: 1832, elevation: 360, sweep: 1) Coordinates: x (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> y (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> z (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> lat (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> lon (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> alt (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> * azimuth (azimuth) float64 181.5 182.6 ... 179.6 180.5 * elevation (elevation) float32 4.936 5.004 ... 5.054 * sweep (sweep) int32 12 * range (range) float32 2.125e+03 ... 4.599e+05 Data variables: differential_phase (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> spectrum_width (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> cross_correlation_ratio (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> clutter_filter_power_removed (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> differential_reflectivity (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> velocity (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> reflectivity (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray>xarray.Dataset- azimuth: 360
- range: 1832
- elevation: 360
- sweep: 1
- x(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - y(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - z(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - lat(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - lon(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - alt(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - azimuth(azimuth)float64181.5 182.6 183.6 ... 179.6 180.5
array([181.546326, 182.551575, 183.554077, ..., 178.558044, 179.552307, 180.543823]) - elevation(elevation)float324.936 5.004 5.07 ... 5.054 5.054
array([4.935608, 5.004272, 5.07019 , ..., 5.053711, 5.053711, 5.053711], dtype=float32) - sweep(sweep)int3212
array([12], dtype=int32)
- range(range)float322.125e+03 2.375e+03 ... 4.599e+05
array([ 2125., 2375., 2625., ..., 459375., 459625., 459875.], dtype=float32)
- differential_phase(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - spectrum_width(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - cross_correlation_ratio(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - clutter_filter_power_removed(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - differential_reflectivity(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - velocity(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - reflectivity(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray
- 🔑 13
<xarray.Dataset> Dimensions: (azimuth: 360, range: 1832, elevation: 360, sweep: 1) Coordinates: x (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> y (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> z (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> lat (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> lon (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> alt (azimuth, range) float64 dask.array<chunksize=(360, 1832), meta=np.ndarray> * azimuth (azimuth) float64 203.5 204.5 ... 201.5 202.5 * elevation (elevation) float32 6.345 6.432 ... 6.372 * sweep (sweep) int32 13 * range (range) float32 2.125e+03 ... 4.599e+05 Data variables: differential_phase (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> spectrum_width (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> cross_correlation_ratio (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> clutter_filter_power_removed (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> differential_reflectivity (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> velocity (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray> reflectivity (azimuth, range) float32 dask.array<chunksize=(360, 1832), meta=np.ndarray>xarray.Dataset- azimuth: 360
- range: 1832
- elevation: 360
- sweep: 1
- x(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - y(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - z(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - lat(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - lon(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - alt(azimuth, range)float64dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - azimuth(azimuth)float64203.5 204.5 205.5 ... 201.5 202.5
array([203.546448, 204.546204, 205.548706, ..., 200.552673, 201.541443, 202.541199]) - elevation(elevation)float326.345 6.432 6.485 ... 6.372 6.372
array([6.344604, 6.432495, 6.48468 , ..., 6.37207 , 6.37207 , 6.37207 ], dtype=float32) - sweep(sweep)int3213
array([13], dtype=int32)
- range(range)float322.125e+03 2.375e+03 ... 4.599e+05
array([ 2125., 2375., 2625., ..., 459375., 459625., 459875.], dtype=float32)
- differential_phase(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - spectrum_width(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - cross_correlation_ratio(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - clutter_filter_power_removed(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - differential_reflectivity(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - velocity(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - reflectivity(azimuth, range)float32dask.array<chunksize=(360, 1832), meta=np.ndarray>
Array Chunk Bytes 2.52 MiB 2.52 MiB Shape (360, 1832) (360, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray
klch_xradar['0']
<xarray.Dataset>
Dimensions: (azimuth: 720, range: 1832, elevation: 720,
sweep: 1)
Coordinates:
x (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray>
y (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray>
z (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray>
lat (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray>
lon (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray>
alt (azimuth, range) float64 dask.array<chunksize=(720, 1832), meta=np.ndarray>
* azimuth (azimuth) float64 7.251 7.748 ... 6.254 6.748
* elevation (elevation) float32 0.5136 0.5466 ... 0.4834
* sweep (sweep) int32 0
* range (range) float32 2.125e+03 ... 4.599e+05
Data variables:
differential_phase (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray>
spectrum_width (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray>
cross_correlation_ratio (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray>
clutter_filter_power_removed (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray>
differential_reflectivity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray>
velocity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray>
reflectivity (azimuth, range) float32 dask.array<chunksize=(720, 1832), meta=np.ndarray>- azimuth: 720
- range: 1832
- elevation: 720
- sweep: 1
- x(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - y(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - z(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - lat(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - lon(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - alt(azimuth, range)float64dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 10.06 MiB 10.06 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float64 numpy.ndarray - azimuth(azimuth)float647.251 7.748 8.253 ... 6.254 6.748
array([7.250977, 7.748108, 8.253479, ..., 5.756836, 6.253967, 6.748352])
- elevation(elevation)float320.5136 0.5466 ... 0.4834 0.4834
array([0.513611, 0.54657 , 0.535583, ..., 0.483398, 0.483398, 0.483398], dtype=float32) - sweep(sweep)int320
array([0], dtype=int32)
- range(range)float322.125e+03 2.375e+03 ... 4.599e+05
array([ 2125., 2375., 2625., ..., 459375., 459625., 459875.], dtype=float32)
- differential_phase(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - spectrum_width(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - cross_correlation_ratio(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - clutter_filter_power_removed(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - differential_reflectivity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - velocity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray - reflectivity(azimuth, range)float32dask.array<chunksize=(720, 1832), meta=np.ndarray>
Array Chunk Bytes 5.03 MiB 5.03 MiB Shape (720, 1832) (720, 1832) Count 1 Tasks 1 Chunks Type float32 numpy.ndarray
Visualize our Output#
Start first with xarray! We use matplotlib directly, specifying our axes
fig = plt.figure(figsize=(10,8))
ax = plt.subplot(111, projection=ccrs.PlateCarree())
khgz_xradar['0'].reflectivity.plot(ax=ax,
y='lat',
x='lon',
cmap='pyart_HomeyerRainbow',
vmin=-20,
vmax=60)
ax.add_feature(cfeature.LAND)
ax.add_feature(cfeature.STATES)
<cartopy.mpl.feature_artist.FeatureArtist at 0x195b95730>
khgz_xradar['0'].reflectivity.hvplot.quadmesh(x='lon',
y='lat',
rasterize=True,
width=600,
height=400,
clim=(-20, 60),
projection=ccrs.PlateCarree(),
cmap='pyart_HomeyerRainbow',
features=['land', 'lakes','borders','ocean'])